Model Comparison
MiMo-V2.5-Pro vs Qwen3 VL 235B A22B InstructWhich is better in 2026?
Both models are evenly matched across the benchmarks. MiMo-V2.5-Pro is 1.1x cheaper per token.
Verdict: MiMo-V2.5-Pro vs Qwen3 VL 235B A22B Instruct — which is better?
MiMo-V2.5-Pro (by Xiaomi) and Qwen3 VL 235B A22B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
MiMo-V2.5-Pro outperforms in 2 benchmarks (MMLU, MMLU-Redux), while Qwen3 VL 235B A22B Instruct is better at 2 benchmarks (LiveCodeBench v6, MMLU-Pro). Both models are evenly matched across the benchmarks.
On price, MiMo-V2.5-Pro is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5-Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiMo-V2.5-Pro if…
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Choose Qwen3 VL 235B A22B Instruct if…
- you want predictable pricing at $0.30/M input and $1.49/M output
Performance Benchmarks
Comparative analysis across standard metrics
MiMo-V2.5-Pro outperforms in 2 benchmarks (MMLU, MMLU-Redux), while Qwen3 VL 235B A22B Instruct is better at 2 benchmarks (LiveCodeBench v6, MMLU-Pro).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiMo-V2.5-Pro ($0.43/1M tokens) is 1.4x more expensive than Qwen3 VL 235B A22B Instruct ($0.30/1M tokens).
For output processing, MiMo-V2.5-Pro ($0.87/1M tokens) is 1.7x cheaper than Qwen3 VL 235B A22B Instruct ($1.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Instruct is more expensive than MiMo-V2.5-Pro.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 787.2B more parameters than Qwen3 VL 235B A22B Instruct, making it 333.6% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5-Pro accepts 1,048,576 input tokens compared to Qwen3 VL 235B A22B Instruct's 262,144 tokens. Qwen3 VL 235B A22B Instruct can generate longer responses up to 262,144 tokens, while MiMo-V2.5-Pro is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Instruct supports multimodal inputs, whereas MiMo-V2.5-Pro does not.
Qwen3 VL 235B A22B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2.5-Pro
Qwen3 VL 235B A22B Instruct
License
Usage and distribution terms
MiMo-V2.5-Pro is licensed under MIT, while Qwen3 VL 235B A22B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiMo-V2.5-Pro was released on 2026-04-27, while Qwen3 VL 235B A22B Instruct was released on 2025-09-22.
MiMo-V2.5-Pro is 7 months newer than Qwen3 VL 235B A22B Instruct.
Apr 27, 2026
3 months ago
7mo newerSep 22, 2025
10 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita. Qwen3 VL 235B A22B Instruct is available from DeepInfra, Novita.
MiMo-V2.5-Pro
Qwen3 VL 235B A22B Instruct
Outputs Comparison
Key Takeaways
Qwen3 VL 235B A22B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiMo-V2.5-Pro and Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiMo-V2.5-Pro vs Qwen3 VL 235B A22B Instruct.